Going from CER to Patient-Centered Care: Implications of Heterogeneity (Text Version)

Going from CER to Patient-Centered Care: Implications of Heterogeneity

Slide Presentation from the AHRQ 2010 Annual Conference

On September 28, 2010, David Atkins made this presentation at the 2010 Annual Conference. Select to access the PowerPoint® presentation (422 KB). Free PowerPoint® Viewer (Plugin Software Help).

Slide 1

Going from CER to Patient—Centered Care: Implications of Heterogeneity

• Trial: Is treatment A better than treatment B?
• Clinician: Is treatment A better than B for this specific patient?
• Health care system: Is treatment A better than B, and for whom, in which settings?

Images: The Department of Veterans Affairs and Department of Defense logos. These two logos appear on all subsequent slides.

Slide 2

Heterogeneity and Policy

• Policies seek to promote use of "best" treatment option.
• "Best" treatment for population may not be same as that for individuals.
• Most important when variation is:
  • Common.
  • Leads to big enough differences to change decision making.
  • Treatment choices can't be adjusted.

Slide 3

Audience Response

• Is CABG the best option for all patients with diabetes?
• How might a health system encourage greater use of CABG in appropriate patients?
• Would it be appropriate to discourage CABG in groups where PCI produces equivalent outcomes?

Slide 4

Is CABG the "Best" Choice for Patients with Diabetes?

• Need to consider harms and complications.
• Patient preferences for different outcomes:
  • e.g., short-term risks of CABG.
• Variation due to quality of surgeon:
  • Applicability of trial evidence.

Slide 5

Policies Used To Influence Use of "Best" Treatments

• Guidelines
• Audit and Feedback
• Coverage decisions:
  • Non-coverage
  • Conditional coverage
  • Tiered coverage
• Quality Measurement:
  • Incentives, Public reporting

Slide 6

Distinguishing Important from Unimportant Heterogeneity

• Does it change direction of NET benefit enough to alter decisions?
• Is it common?
• Is it predictable?
• Can it be detected and treatment modified in response to variation in benefits or harms?

Slide 7

Example: SSRIs for Depression

• Comparable effectiveness of most agents in depression responsiveness but individual variation.
• Affect decisions: YES—Variability in response and side effects.
• Common: YES
• Predictable: NO
• Can variable response be monitored? YES

Slide 8

Dealing With Variation in SSRI as Response in Policy

• Not possible to identify who will do better on a different agent.
• Cover only 1-2 SSRIs in formulary?
• Recommend starting all patients with a specific SSRI as initial therapy?

Slide 9

Conclusions

• Heterogeneity is a real and important phenomenon in research and policy.
• Examination of pre-specified factors in individual trials, SRs and meta-analysis can detect HTE:
  • Be cautious about post-hoc sub-groups.
• Policies need to accommodate HTE.
  • But doesn't mean that complete, unfettered clinician choice is best.